import mat73
import scipy


# file_name = "/data2/npc/lixiang/playground/aaa/mind-whisper/rawdata/zuco2/task1 - NR/Raw data/YAK/YAK_NR1_EEG.mat"
# data = scipy.io.loadmat(file_name, squeeze_me=True, struct_as_record=False)

# print('aaa')




# #-------------查看缺失值id-----------------
file_name = "/data2/npc/lixiang/playground/aaa/mind-whisper/rawdata/zuco2/task1 - NR/Matlab files/resultsYAK_NR.mat"
data = mat73.loadmat(file_name)
mean_a1 = data['sentenceData']['mean_a1']

# all = []

# for k in [
#     "allFixations",
#     "content",
#     "mean_a1",
#     "mean_a1_diff",
#     "mean_a2",
#     "mean_a2_diff",
#     "mean_b1",
#     "mean_b1_diff",
#     "mean_b2",
#     "mean_b2_diff",
#     "mean_g1",
#     "mean_g1_diff",
#     "mean_g2",
#     "mean_g2_diff",
#     "mean_t1",
#     "mean_t1_diff",
#     "mean_t2",
#     "mean_t2_diff",
#     "omissionRate",
#     "rawData",
# ]:

#     Nanid = []
#     for idx, each in enumerate(data["sentenceData"][k]):
#         if str(each) == "nan":
#             Nanid.append(idx)
#     print(k)
#     print(Nanid)
#     all += Nanid

# all = list(set(all))
# print(all)

# file_name = "/data2/npc/lixiang/playground/aaa/mind-whisper/rawdata/zuco2/task1 - NR/Preprocessed/YAK/oip_YAK_NR1_EEG.mat"
# data = mat73.loadmat(file_name)
# raweeg = data['EEG'].data


# file_name = "/data2/npc/lixiang/playground/aaa/mind-whisper/rawdata/zuco2/task1 - NR/Preprocessed/wordbounds_NR1.mat"
# data = scipy.io.loadmat(file_name)
# raweeg = data['EEG'].data
